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• This work estimates water and light use efficiency in garlic based on ground data. • The model integrates series of satellite vegetation indices in crop growth models. • The normalization of these efficiencies for the atmospheric conditions is analyzed. • Additional analysis are the use of cold temperature stress on the noted models. • The results are promising for the operative estimation of garlic biomass production. The objective of this paper was to determine the water use efficiency (WUE) and light use efficiency (LUE) values of garlic (Allium sativum L.) and to analyze the normalization of these efficiencies for the atmospheric conditions. We analyzed the use of daily reference evapotranspiration (ETo) and the vapor pressure deficit (VPD) for these purposes. WUE and LUE were valued based on the experimental measurements of dry biomass production and the estimation of transpiration and radiation interception based on time series of Remote Sensing satellite images. The experimental data were obtained in two commercial fields each planted with a different variety of garlic (var. morado and var. spring) growing in different weather conditions in the province of Albacete (in the south-east of Spain). The correlation between the accumulated values of biomass and the estimated values of crop transpiration and radiation absorption resulted in strong linear relationships. The slope of these correlations resulted in values of WUE and LUE, WUE = 5.51 g m−2 mm−1 and LUE = 2.26 g·MJ−1 for both analyzed varieties. The results demonstrated that the inclusion of temperature stress coefficient is required when the WUE and LUE parameters are normalized using the ETo and the VPD variables. However, atmospheric normalization did not conclusively improve results in this study. Results obtained in this paper provided empirical evidence regarding the feasibility of estimating biomass production in garlic based on the same physiological principles used for other crops. [ABSTRACT FROM AUTHOR]

• This work estimates harvest index in wheat crops using a RS-based approach. • This paper analyses an extensive HI dataset obtained of commercial fields. • The model integrates series of satellite vegetation indices into crop growth models. • Additional analysis are the effect of water stress in the proposed models. • The results are promising for the operational estimation of wheat production. This paper presents an operational methodology for the estimation of the harvest index (HI) in commercial fields planted with wheat crops (Triticum aestivum L.) using a Remote Sensing based approach. The approach proposed variants from the methodologies reported by Kemanian et al., (2007) and Sadras and Connor (1991) for the estimation of the HI using the ratio between variables related with biomass production, i.e. absorbed photosynthetically active radiation (APAR), crop transpiration (T) and crop transpiration coefficient (K t) as defined in the FAO-66 manual. The estimation of these variables along the growing season integrates time series of Remote Sensing satellite images and meteorological data into the crop growth models. The proposed models for estimation of HI were calibrated using an extensive HI dataset obtained from 19 commercial fields (empirical data) planted with wheat. The fields were subject to different water and nutrient management, resulting in empirical HI values from 0.23 to 0.55. Future applications of the proposed approach are the operational estimation of wheat production at both regional and local scales and the estimation of the within-field variability of crop production considering the variability of HI values within the field. [ABSTRACT FROM AUTHOR]